Method for quantization of histogram bin value of image

ABSTRACT

A method for quantization of a color histogram bin value of an image or video, and more particularly, a method for non-uniform quantization of a color histogram bin value of an image (or video) according to the frequency of color occurrence is provided. The methods effectively represent the characteristics of a color histogram of an image in comparison to conventional art, and improve the performance of image retrieval when an image (video) retrieval search is conducted.

This application is a Continuation of prior application Ser. No.10/988,587, filed Nov. 16, 2004, which is a Continuation of priorapplication Ser. No. 09/712,932, filed Nov. 16, 2000, now U.S. Pat. No.6,952,495, which claims priority to Korean application No. 51428/1999,filed Nov. 19, 1999, all of which are hereby incorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a method for quantization of ahistogram bin value of an image or video, and more particularly, to amethod for non-uniform quantization of a color histogram bin value of animage (or video) according to the frequency of color occurrence.

2. Description of the Background Art

Conventionally, it is possible to reduce the amount of information forexpressing a color histogram of an image if the color histogram binvalue is quantized. However, the color histogram bin value is merelyquantized uniformly, irrespective of the frequency of color occurrencein images.

FIG. 1 is a view illustrating an example of a table of uniformquantization of a color histogram bin value according to theconventional art. In other words, the color histogram bin value isquantized by partition into uniform intervals.

For example, when the color histogram bin value ranges from 0 to 1 andthe bin value is expressed by 16 numbers of branch using 4-bits, it isquantized by partition into uniform sections of 0.0625 ( 1/16=0.0625).

However, the color histogram bin value is generally low in natural image(In FIG. 2, for example, there is almost no bin having a bin value ofmore than 0.1), particularly, bins having a bin value of 0 occupy themost part of the whole color histogram bins (In FIG. 2, for example,more than 95% of the whole color histogram bins).

Therefore, a color histogram bin value near to 0 has to be quantizedfinely by a large number so that the intervals of the bin value aresmall. In addition, a color histogram bin value near to 1 can bequantized coarsely by a small number so that the intervals of the binvalue are large.

However, as described above, in the method for quantization of a colorhistogram bin value according to the conventional art, there arises aproblem that the information of the color histogram is lost, since thecolor histogram is uniformly quantized irrespective of the frequency ofthe color histogram bin value.

For example, if the color histogram bin value is quantized withoutconsidering its characteristics, such as the existence or non-existenceof a certain particular color in a certain image and the frequentoccurrence or infrequent occurrence of a color in the image, the uniqueinformation of the color histogram, which is an important information asone of the characteristics of the image, cannot be precisely preserved.

In addition, since the unique information of the color histogram cannotbe precisely preserved, it causes a problem that it is difficult for theinformation about quantization of color histogram bin value to obtainsufficient reliability in reflecting the characteristics of the image,where the information about quantization of color histogram bin value isusually used as a characteristic information of an image. In addition,if the information poorly reflecting the color histogram characteristicsof the image is used, the performance of image searching is degraded forthe image retrieval.

In addition, if the information poorly reflecting the color histogramcharacteristics of the image is used, there arises a problem that theimage characteristics are not consistent with the visual/sensiblecharacteristics of a human being.

SUMMARY OF THE INVENTION

Accordingly, it is an object of the present invention to provide amethod for quantization of a color histogram bin value of an image (orvideo) in which the color histogram bin value is non-uniformly quantizedin consideration of the frequency of color occurrence.

It is another object of the present invention to provide a method forquantization of a color histogram bin value of an image in which thecharacteristics of the color histogram reflects well the characteristicsof the image by means of non-uniformly quantizing the color histogrambin value of the image (or video) in consideration of the frequency ofcolor occurrence.

It is another object of the present invention to provide a method forquantization of a color histogram bin value of an image in which theimage (or video) retrieval performance is improved by applying thequantization of the color histogram bin value.

It is another object of the present invention to provide a method forquantization of a color histogram bin value of an image which makes itpossible to construct a database of the information of thecharacteristics of the image, that is consistent with thevisual/sensible characteristics of a human being by applying thequantization of the color histogram bin.

It is another object of the present invention to provide a method forquantization of a color histogram bin value of an image which canimprove the performance of the image retrieval with the same amount ofinformation in representing and storing the color histogram as that inthe conventional quantization method.

To achieve the above object, there is provided a method for quantizationof a color histogram bin value of an image which is achieved bynon-uniformly quantizing the color histogram bin value according to thefrequency of color occurrence.

To achieve the above object, there is provided another method forquantization of a color histogram bin value of an image which isachieved by uniformly quantizing the color histogram bin values into alarge number of sections if the bin value is greater than ‘0’ and lessthan a predetermined threshold, mapping the color histogram bin valuesinto a single quantum if the bin value is greater than the threshold andmapping the color histogram bin value ‘0’ into a single quantum.

To achieve the above object, there is provided another method forquantization of a color histogram bin value of an image which isachieved by non-uniformly quantizing the section where the colorhistogram bin value of the image is greater than ‘0’ and less than apredetermined threshold of the color histogram bin value of the image.

Additional advantages, objects and features of the invention will becomemore apparent from the following description

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention will become better understood with reference tothe accompanying drawings which are given only by way of illustrationand thus are not limitative of the present invention, wherein:

FIG. 1 is a view illustrating an example of a table of uniformquantization of a color histogram bin value according to theconventional art;

FIG. 2 is a view illustrating a percentage distribution of bins withrespect to a color histogram bin value of an image according to anembodiment of the present invention; and

FIG. 3 is a view illustrating a table of non-uniform quantization of thecolor histogram bin value of the image according to the embodiment ofthe present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 2 is a view illustrating a percentage distribution of bins withrespect to a color histogram bin value of an image according to anembodiment of the present invention. In other words, it is a viewillustrating an example in which the color histogram bin values of 512colors in HMMD (Hue/Max/MIN/Difference) color space are calculated with5466 images, and the frequency of color occurrence with respect to thecalculated bin values is expressed as a percentage. Here, the above binvalue is a normalization value of the frequency of color occurrence andeach bin value is ranged from 0 to 1.

As illustrated therein, the distribution of the color histogram binvalues shows the characteristics of the color distribution. In otherwords, the occurrence of the color histogram bin value of ‘0’ is veryfrequent (e.g., the bins having a bin value of 0 account for 95% of allcolor histogram bins). And the occurrence of the color histogram binvalue of ‘0.1’ is very rare (there is almost no bins having a bin valueof more than 0.1). In other words, when a natural visual image (orvideo) of a scenery, person, object, etc. is represented as a normalizedcolor histogram, most of color histogram bins have a value of ‘0’, andfew of color histogram bins have a value greater than 0.1.

Here, the fact that the color histogram bin value is ‘0’ means that thecolor corresponding to that bin is not existed in an image. Inparticular, it can be known that there are a few bins having a value ofmore than a predetermined threshold (e.g. 0.1).

FIG. 3 is a view illustrating a table of non-uniform quantization of thecolor histogram bin value of the image according to the embodiment ofthe present invention, which will now be described in detail withreference to FIG. 2.

As illustrated therein, in the case where the color histogram bin valueis non-uniformly quantized according to the color histogram bin value,the characteristics of the color histogram can be expressed moreeffectively as compared to the uniform quantization of a bin valueaccording to the conventional art.

Particularly, if the color histogram bin value is ‘0’, it can be theimportant information that the colors according to the bins don't appearin the image and the majority of all bins in the color histogram have abin value of ‘0’, therefore, the color histogram bin value of ‘0’ ismapped into a single quantum in quantizing the color histogram binvalue. In real implementation, for a practical reason, ‘0’ may beconsidered to the range between ‘0’ and a number that is very close to‘0’ (e.g. 0.000000001).

Hence, since there are a few bins having a color histogram bin value ofmore than a predetermined threshold (0.1 in FIG. 2), that is, only a fewcolors have a high frequency of occurrence in the image, the all binvalues of more than a predetermined threshold are mapped into a singlequantum.

In addition, if the color histogram bin value is ‘0’, it is expressed asquantum value (binary number 0000). The color histogram bin valuesgreater than ‘0.1’ (0.1˜1.0) are expressed as quantum value ‘1’ (binarynumber 1111). The color histogram bin value ranging from 0.0001 to0.0999 (That is, the value of more than ‘0’ and less than a threshold)is quantized as a plurality of appropriate sections, that is, dividedfinely.

Meanwhile, when a non-uniform quantization of the color histogram binvalue is conducted, an uniform quantization can be conducted in thesections in which the color histogram bin value is greater than ‘0’ andless than the threshold (0.0999).

However, to improve performance further, in the sections in which thecolor histogram bin value is greater than ‘0’ and less than thethreshold (0.0999), a non-uniform quantization can be conducted inconsideration of the frequency of color occurrence.

As described above, the present invention has an effect of preservingthe characteristics of the color histogram of a image (or video) betteras compared to the conventional art, by means of non-uniformquantization to a bin value in consideration of the frequency of coloroccurrence of the image, e.g., the distribution of color histogram binvalues.

In addition, when an image (or video) retrieval is conducted on theinformation of the color histogram representing effectively thecharacteristics of the color histogram of the image, the performance ofimage retrieval can be improved.

In addition, the performance of image retrieval can also be improved bymeans of the same amount of information as in the method for uniformquantization of a bin value according to the conventional art.

For example, the bin value range which a large number of bins belong tois divided into a plurality sections and is quantized finely, and theother side, the bin value range which a small number of bins belong tois quantized as a single section (In the conventional art, the colorhistogram bin value is uniformly quantized irrespective of the frequencyof color histogram bin value). That is, if the range which a largenumber of bins belong to is divided into a plurality of sections and isquantized, then the original color information of the image (video) canbe preserved well, and therefore the performance of the image retrievalis improved when the image (video) retrieval is conducted.

In addition, there is an effect of reducing the amount of informationrepresenting the characteristics of the color histogram of the image soas to acquire the same performance of the image retrieval as in theconventional method for uniform quantization of a bin value,

For example, while 100 bytes are used to store the information of theuniform quantization of a color histogram bin value in the conventionalart, a space smaller than 100 bytes can be used to store the sameinformation in the method for non-uniform quantization of a colorhistogram bin value of an image according to the present invention. Thereason thereof is because the bin value is expressed as a single bin ora few bins in the method for non-uniform quantization of a high binvalue (e.g. the value greater than 0.1), while the bin value isexpressed as a plurality of quanta in the method for uniformquantization of bins having a bin value of more than a threshold, thusmaking it possible to reduce the storage.

Moreover, in the case that a database is constructed by gatheringinformation of the image characteristics, there is an effect ofgenerating information more consistent with the visual/sensiblecharacteristics of a human being by including the color histogramadapted by quantization of a bin value according to the presentinvention to the constructed database.

The present invention is not limited to the normal color histogram. Anyhistogram type descriptor can be applied in the present invention byanalyzing histogram bin value distribution. As another embodiment ofapplying the present invention instead of the described normal colorhistogram, a non-uniform color structure histogram bin valuequantization is described as follows.

The color structure histogram is computed by visiting (a subset on alllocations in the image, retrieving colors Cm of all pixels contained inthe structure elements (e.g. 8 by 8 window) overlaid on each location,and incrementing the bin value corresponding to color Cm. Afteraccumulating the bin values, they are non-uniformly quantized in to an8-bit value as follows.

After normalizing bin values by dividing theoretic maximum bin value,each bin value becomes the number between 0 and 1. Then, the bin valuerange is divided into 6 regions, and subsequently a different number ofquantization levels is allocated uniformly to each region. Thethresholds defining each region of the bin value range (between 0.0 and0.1) are: th0=0.000000001, th1=0.037, th2=0.08, th3=0.195 and th4=0.32.The numbers of quantization levels allocated to each region aredescribed in the following table:

Region Number of levels 0 1 1 25 2 20 3 35 4 35 5 140

As the present invention may be embodied in several forms withoutdeparting from the spirit or essential characteristics thereof, itshould also be understood that the above-described embodiments are notlimited by any of the details of the foregoing description, unlessotherwise specified, but rather should be construed broadly within itsspirit and scope as defined in the appended claims, and therefore allchanges and modifications that fall within the meets and bounds of theclaims, or equivalences of such meets and bounds are therefore intendedto be embraced by the appended claims.

1. A method for quantization of bin values of a color histogram, themethod comprising: normalizing bin values by a maximum bin value;separating the normalized bin values into a plurality of regions; anduniformly quantizing each region, wherein intervals of each region arequantized more finely closer to zero.
 2. The method according to claim1, wherein the range of the normalized bin values is from 0 to 1.